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210512 ||| eng |
| 020 |
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|a 9783039439720
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|a 9783039439713
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| 020 |
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|a books978-3-03943-972-0
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| 100 |
1 |
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|a Stateczny, Andrzej
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| 245 |
0 |
0 |
|a Radar and Sonar Imaging and Processing
|h Elektronische Ressource
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| 260 |
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|a Basel, Switzerland
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2021
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| 300 |
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|a 1 electronic resource (468 p.)
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| 653 |
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|a narrow-band radar
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| 653 |
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|a safe ship trajectory
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| 653 |
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|a radar
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|a Retinex
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|a autonomous surface vehicles
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| 653 |
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|a data fusion
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| 653 |
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|a super-resolution
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| 653 |
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|a 1D scaled Fourier transform (1D SCFT)
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| 653 |
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|a interferometric inverse synthetic aperture radar (InISAR)
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| 653 |
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|a accuracies
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| 653 |
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|a numerical transfer function
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| 653 |
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|a radars calibration
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| 653 |
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|a image registration
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| 653 |
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|a deceptive jamming
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| 653 |
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|a earth observation
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| 653 |
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|a ground penetrating radar
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| 653 |
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|a artificial neural network
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| 653 |
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|a signal recognition
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| 653 |
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|a target detection
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| 653 |
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|a measurement reliability
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| 653 |
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|a adaptive initialization
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| 653 |
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|a quadratic phase error
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| 653 |
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|a vessel mounted acoustic Doppler current profiler
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| 653 |
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|a marine radar current measurement
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| 653 |
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|a deep convolutional neural network
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| 653 |
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|a automotive radar
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| 653 |
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|a strong scattering centers fusion
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| 653 |
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|a Doppler sensor
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| 653 |
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|a meteorological radar
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| 653 |
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|a orbit determination error
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| 653 |
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|a phase analysis
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| 653 |
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|a complex Doppler ambiguity
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| 653 |
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|a non-uniform FFT (NUFFT)
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| 653 |
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|a game theory
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| 653 |
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|a target imaging
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| 653 |
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|a large bandwidth
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| 653 |
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|a underwater sonar image
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| 653 |
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|a numerical evaluation
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| 653 |
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|a space-borne SAR
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| 653 |
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|a focusing
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| 653 |
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|a synthetic aperture radar (SAR)
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| 653 |
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|a terahertz radar imaging
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| 653 |
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|a parallax
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| 653 |
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|a underground cavity detection network
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| 653 |
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|a sensor design
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| 653 |
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|a precision
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| 653 |
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|a X-Band radar
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| 653 |
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|a Research and information: general / bicssc
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| 653 |
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|a computer simulation
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| 653 |
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|a superimposition
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| 653 |
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|a multibeam echo sounder
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| 653 |
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|a bathymetry
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| 653 |
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|a quality control
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| 653 |
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|a Lagrange inversion theorem
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| 653 |
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|a fuzzy sets theory
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| 653 |
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|a target recognition
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| 653 |
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|a target classification
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| 653 |
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|a high-resolution
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| 653 |
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|a 3D sonar
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| 653 |
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|a geostationary satellite
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| 653 |
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|a multireceiver
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| 653 |
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|a approximation
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| 653 |
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|a road traffic monitoring
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| 653 |
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|a image enhancement
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| 653 |
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|a low frequency
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| 653 |
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|a adaptive denoising
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| 653 |
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|a automated underground object classification
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| 653 |
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|a complex deconvolution
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| 653 |
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|a gas emissions
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| 653 |
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|a Synthetic Aperture Radar (SAR)
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| 653 |
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|a acoustic vector sensor
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| 653 |
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|a water column image
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| 653 |
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|a side-scan sonar image
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| 653 |
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|a cloud
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| 653 |
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|a target tracking
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| 653 |
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|a MSG
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| 653 |
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|a range-dependent coupling
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| 653 |
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|a fast-maneuvering target refocusing
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| 653 |
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|a automatic detection
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| 653 |
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|a computer decision support
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| 653 |
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|a side-scan sonar
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| 653 |
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|a features extraction
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| 653 |
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|a sonar
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| 653 |
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|a initial image matching with constraint
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| 653 |
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|a dense local self-similarity
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| 653 |
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|a weighted features fusion
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| 653 |
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|a autonomous navigation
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| 653 |
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|a side scan sonar
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| 653 |
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|a SEVIRI
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| 653 |
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|a improved generalized chirp scaling (GCS)
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| 653 |
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|a gray scale correction
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| 653 |
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|a optical flow
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| 653 |
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|a bottom tracking
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| 653 |
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|a spaceborne real-time SAR imaging
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| 653 |
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|a real-time processing
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| 653 |
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|a image understanding
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| 653 |
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|a data reduction
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| 653 |
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|a detection
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| 653 |
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|a anti-drone systems
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| 653 |
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|a FMCW radars
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| 653 |
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|a periodically gapped data
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| 653 |
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|a SAR
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| 653 |
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|a WaMoS® II
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| 653 |
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|a anti-collision
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| 653 |
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|a one-dimensional convolutional neural network
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| 653 |
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|a signal reconstruction
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| 653 |
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|a drones detection
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| 653 |
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|a synthetic aperture sonar (SAS)
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| 653 |
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|a translational motion parameters estimation
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| 653 |
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|a imaging algorithm
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| 700 |
1 |
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|a Kulpa, Krzysztof
|
| 700 |
1 |
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|a Kazimierski, Witold
|
| 700 |
1 |
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|a Stateczny, Andrzej
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
|
| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
8 |
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|a 10.3390/books978-3-03943-972-0
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| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/3340
|7 0
|x Verlag
|3 Volltext
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/68330
|z DOAB: description of the publication
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|a 000
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|a 700
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|a The Special Issue "Radar and Sonar Imaging Processing" is a collection of 21 articles exploring many topics related to remote sensing with radar and sonar sensors. In this editorial, we present short introductions of the published articles. The series of articles in this SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends while making use of the latest developments in science, including artificial intelligence. It can be said that both radar and sonar imaging and processing still remain a "hot topic" and much research in this area is being conducted worldwide. New techniques and methods for extracting information from radar and sonar sensors and data have been proposed and verified. Some of these will stimulate further research while others have reached maturity and can be considered for industrial implementation and development.
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